The proposed research will attempt to integrate two models of the same-different comparison process--a multifeatural model and a unidimensional model. Both models are consistent with a general, noisy-operator theory. The new model posits that the observer attends to stimulus dimensions in a quantitative manner when the number of dimensions is small, but in a qualitative, all-or-none (featural) manner when the number is large. In both cases, the observer behaves in a Bayesian manner in making decisions within and between dimensions. The main test will vary the number of lines compared at one time. Other tests of the matching process will focus on the search for absence task, in order to pinpoint why the many matches encountered in that task should search to such a great extent.